【摘要】 目的：本研究旨在探讨在宫颈癌（Cervical Cancer,CC）中活性氧（Reactive Oxygen Species,ROS）相关基因的潜在预后价值。方法：从TCGA数据库下载CC的m RNA表达数据及临床信息。获得差异表达的基因后，应用Cox回归和LASSO回归建立CC的预后风险模型，并在临床相关信息中进行评价。CIBERSORT在线免疫细胞浸润估计分析工具用于量化宫颈癌样本中免疫细胞的比例。最后，评估免疫检查点抑制剂和化疗药物在不同风险人群中的敏感性。结果：本研究筛选出6个候选基因（JUN、SOD2、EGFR、BTK、DUOX1和TP53）构建风险模型，作为CC的独立预后标志物；富集分析表明，不同表达的基因在几种OS途径中富集。此外，不同风险组患者在免疫细胞浸润、免疫检查点抑制剂和化疗药物中有差异。结论：基于ROS相关基因构建的风险模型是一个独立的预后因素，有助于为CC的防治提供信息。更多还原

【Abstract】 Objective:This study aimed to explore the potential prognostic value of reactive oxygen species(ROS)-related genes and their impact on the immune microenvironment of cervical cancer(CC). Methods:The m RNA expression data of processed CC were downloaded from The Cancer Genome Atlas(TCGA) database.After obtaining the differentially expressed genes, Cox regression and LASSO regression were applied to model the prognostic risk of CC and evaluated in clinically relevant information.The CIBERSORT online analysis tool for estimating immune cell infiltration was used to quantify the proportions of immune cells in the CC samples. Finally,the sensitivity of immune checkpoint inhibitors(ICIs) and chemotherapeutic agents in different risk groups was evaluated.Results:In this study, six candidate genes(JUN, SOD2, EGFR, BTK, DUOX1 and TP53) were used to construct the risk model.The ROS-related risk score(RRS) model was shown to be an independent prognostic marker for CC in the subsequent analysis. Enrichment analysis suggested that the differentially expressed genes were enriched in several oxidative stress(OS) pathways. In addition, immune cell infiltration, ICIs and chemotherapeutic drugs were generally different in the high-and low-risk groups.Conclusions:The risk model constructed based on ROS-related genes is an independent prognostic factor that can effectively predict the prognosis of CC patients.更多还原